论文解读——CMT:Cross Modal TransformerCMT 是旷视在 ICCV2023 的一篇论文,其基于 PERT,并加入了激光雷达数据,利用 Transformer 很好地融合了两种模态的数据。新手小白建议先看 DETR 系列。论文的继承关系为…
环境调试——CMT:Cross Modal Transformer CMT 的官方源代码已经在github上发布。其源码也是基于 mmdet3d 框架。根据官方 README,笔者也测试了其在 nuscenes 上的精度,与论文所述一致。本文记录笔者将官方源代码跑通过程。新手小白可能不太会 mmdet3d。笔者来个保姆级教程。建议完整看完本文,再动手实践,而不是边看...
Cross-modal transformerDeep learningFeature fusionSpeech emotion recognition has seen a surge in transformer models, which excel at understanding the overall message by analyzing long-term patterns in speech. However, these models come at a computational cost. In contrast, convolutional neural networks ...
CMT，旷视团队在国际计算机视觉会议（ICCV）上发布的新论文，是Transformer架构在多模态数据融合领域的一次重要突破。作为PETR的后续发展，CMT通过巧妙地结合激光雷达数据，实现了对视觉和深度信息的高效整合，构建出一个简洁且性能卓越的模型。对于初学者，推荐先了解DETR系列，CMT的进化脉络是：CMT > PETR >...
@article{yan2023cross,title={Cross Modal Transformer via Coordinates Encoding for 3D Object Dectection},author={Yan, Junjie and Liu, Yingfei and Sun, Jianjian and Jia, Fan and Li, Shuailin and Wang, Tiancai and Zhang, Xiangyu},journal={arXiv preprint arXiv:2301.01283},year={2023}} ...
[ICCV 2023] Cross Modal Transformer: Towards Fast and Robust 3D Object Detection - Woogie-Boogie/CMT
Cross-modal key query strategy3D keypoint selectionLightweight pose iterative6DoF pose estimation has received much attention in recent years. A key challenge is the difficulty of estimating object pose when the target texture is weak. In this work, we present the cross-modal Transformer (CMT-6D...
Cross Modal Transformer: Towards Fast and Robust 3D Object Detection CMT_nuScenes_testset.mp4 This repository is an official implementation of CMT. Performance comparison between CMT and existing methods. All speed statistics are measured on a single Tesla A100 GPU using the best model of official...